Dual chamber ICDs have both atrial and ventricular leads and may thereby monitor the cardiac rhythms that occur in the atria and ventricles separately and independently. As is explained in Chapter 17 of “Nonpharmacological Therapy of Arrhythmias for the 21st Century” by I. Singer, S. S. Barold, and A. J. Camm (editors), (Futura Publishing Co., Inc., Armonk, N.Y. 1998), these devices enable P waves, originating in the atria, and R waves, originating in the ventricles, to be independently monitored, such that the P to P and R to R time intervals can be separately monitored, and such that the relative phase relationship of the P-waves and R-waves may also be monitored closely and studied, harmful patterns recognized and identified, and appropriate shock or pacing treatments administered automatically.
Fairly sophisticated techniques have been adopted, in the case of ventricular waveform monitoring, to distinguish ventricular tachycardia (VT) and ventricular fibrillation (VF) from less harmful conditions, such as atrial fibrillation, atrial flutter, and rapid, but not necessarily life threatening, sinus tachycardia (ST). One difficulty with this type of equipment is distinguishing these conditions from each other. The following articles discuss various approaches to improving the performance of ICDs in this area: “Intracardiac Electrogram transformation” by Milton M. Morris, Janice M. Jenkins, and Lorenzo A. DiCarlo, Journal of Electrocardiology, Vol. 29 Supplement, pages 124 to 129 (1996). “Discrimination of ventricular tachycardia from sinus tachycardia by antitachycardia devices: value of median filtering” by Chih-ming James Chiang, Janice M. Jenkins, and Lorenzo A. DiCarlo, Medical Engineering Physics, Vol. 16, pages 513–517 (1994). “A comparison of four New Time-domain Techniques for discriminating Monomorphic Ventricular Tachycardia from Sinus Rhythm Using Ventricular Waveform Morphology” by Robert D. Throne, Janice M. Jenkins, and Lorenzo A. DiCarlo, IEEE Transactions on Biomedical Engineering, Vol. 38, pages 561–570 (IEEE No. 6, June 1991). These articles describe various ways in which the morphology of the ventricular wave can be examined, changes studied, and such things as the degree of change from a normal pattern, as well as the rapidity at which such changes occur, can be determined.
The Chiang et al. article focuses upon changes in the heartbeat interval, where the median (as opposed to the average) of a sequence of five heartbeat intervals is measured and examined for signs of a sudden change, which can signal VT as opposed to ST.
The Throne et al. article teaches the use of correlation waveform analysis (CWA). In this procedure, a “template” waveform, one representing a normal heart rhythm, is correlated against the waveforms actually detected. While this article says that CWA can reliably distinguish between normal and abnormal rhythms, CWA is highly computationally intensive, requiring many multiplications. With battery-powered ICDs, this excess of computations can drain the unit's battery too rapidly. The article explains this problem and explores a number of mathematical algorithms that are less computationally intensive but that give results approaching those achievable with CWA. Templates of the type described in this article also tend to be specific to an individual, and cannot be shared with others.
The Morris, et al. article explores how mathematical transformations, and in particular the Karhunen-Loeve transformation, can be used together with CWA to measure the amplitude of selected morphological features and, by focusing upon transformed values that are associated with particular features, to reduce the number of computations that need to be performed by the CWA between a template and an actual waveform. The transformation reduces the number of coordinate values that need to be correlated and examined. But the Karhunen-Loeve transformation itself is fairly computationally intensive and does not lend itself readily to computational shortcuts such as those utilized, for example, in the fast Fourier transform.
Medtronics, Inc. sells an ICD that uses the Haar wavelet transformation to perform CWA against a template. The Haar transforms are used in this ICD to distinguish ventricular tachycardia (VT) from super ventricular tachycardia (SVT) events, such as atrial fibrillation or flutter or rapid rate sinus tachycardia.
With an atrial lead present, it is also now feasible to study the atrial waveforms more closely. An object of the present invention is to analyze signals received from a bipolar atrial lead to analyze the waveform morphology using the minimum possible number of calculations to conserve battery power and yet reliably to distinguish between atrial ST and non-ST conditions, while also enabling the same apparatus to be used with many different individuals.